Physiological activity of various organs, such as the heart or brain, may be monitored, and this physiological activity may be analysed to look for patterns that may assist in diagnosing various conditions. Typically, the medical diagnostic machine monitors the physiological activity of various organs. The medical diagnostic machine includes, but is not limited to, magnetic resonance imaging machine, computed tomography machine, X-ray machine, nuclear medicine machine, and the like.
In medical environments, users often demand high availability of medical diagnostic machines. However, the medical diagnostic machine components may require periodic maintenance, such as repair or replacement. Indeed, the performance of the medical diagnostic machine components may degrade due to wear, thereby reducing its efficiency.
Being able to predict the current health condition of some key components in the medical diagnostic machine saves good amount of money in servicing the machines. This will enable proactive service and maintenance of the medical diagnostic machine before the key components breakdown. If components break, it not only costs lot of money to replace them but also causes the system to shut down, which will result in lost revenue for a healthcare facility environment. The healthcare facility environment includes, but is not limited to, hospitals, healthcare providers, clinics, diagnostic centres, and the like. Currently, the available solutions have remote monitoring capabilities i.e., monitor the components information remotely, setup triggers and alerts and respond to critical conditions. But, the available solutions don't help in knowing when a next problem can occur and also can't do predictions. Non-availability of the predictive models, demands scheduled trips to be made by the technicians to the healthcare facility environment to evaluate conditions of the components. As a consequence, the information can't be utilized remotely and increases the unnecessary preventive maintenance trips to the healthcare facility environment.
In the light of aforementioned discussion there exists a need for certain system with novel methodologies that would overcome or ameliorate the above-mentioned disadvantages.